發(fā)布時間：2018-04-28 22:05

  本文選題：離線編程 + STL模型　； 參考：《廣東工業(yè)大學》2017年碩士論文

【摘要】：機器人編程方法可分為在線示教編程與離線編程,常用的在線示教編程方法具有精度低、示教繁瑣等缺點。離線編程方法能克服在線示教編程的缺點,從而提高生產(chǎn)效率與保證加工精度。離線編程主要采用從工件的三維CAD模型直接提取機器人運動軌跡的方法完成機器人對工件的表面加工。本文深入研究面向機器人離線編程系統(tǒng)的關鍵技術——軌跡規(guī)劃。主要研究內容如下:1、首先,本文研究了一種基于平衡二叉樹動態(tài)搜索的STL模型生成路徑的算法。STL格式文件包含著待加工曲面的表面信息,可作為獲取路徑的來源文件。通過三維CAD建模獲取包含待加工曲面的STL模型然后通過多個平行切平面與STL模型的三角面片相交,并通過切片平面與三角面片的求交運算得到路徑的數(shù)據(jù)點組。運用平衡二叉樹動態(tài)搜索算法對這些排列雜亂無章的數(shù)據(jù)點組進行優(yōu)化排序后形成一條完整的路徑線。2、其次,本文采用3次NURBS曲線的反求算法對路徑進行優(yōu)化。按照STL模型的切片算法得到的路徑,是由分布不規(guī)則的離散點連接而成的。為了使路徑更加連貫,采用3次NURBS曲線對原路徑進行優(yōu)化。提出自適應的參數(shù)化法算法確定節(jié)點矢量,在已知路徑型值點的情況下,求得能夠準確描述路徑的3次NURBS曲線的節(jié)點矢量和控制點。3、再次,本文研究基于弦截迭代法的機器人軌跡規(guī)劃。在已知能夠準確描述路徑的3次NURBS曲線的表達式的基礎上,根據(jù)弓高誤差預測出插補點處的節(jié)點參數(shù),使用弦截迭代法對預測的節(jié)點參數(shù)進行迭代求出真實的節(jié)點參數(shù),保證理想速度與實際速度之間的波動率在一定范圍內。4、最后,運用MFC與Open GL技術開發(fā)了軌跡生成系統(tǒng)。根據(jù)本文研究的路徑生成、路徑優(yōu)化與軌跡規(guī)劃的算法,提出系統(tǒng)的體系結構、系統(tǒng)界面、模塊功能,對提出的機器人運動軌跡生成方法進行驗證。在系統(tǒng)中導入猴型雕刻工件的STL模型生成機器人運動軌跡并進行實際加工,并且與僅基于STL切片算法得到的運動軌跡進行對比驗證本文研究算法的有效性。
[Abstract]:Robot programming methods can be divided into online teaching programming and off-line programming. The common online teaching programming methods have the disadvantages of low precision and tedious teaching. Off-line programming method can overcome the shortcomings of online teaching programming, thus improve production efficiency and ensure machining accuracy. Off-line programming mainly uses 3D CAD model of workpiece to extract robot motion trajectory directly to finish the surface machining of workpiece. In this paper, trajectory planning, the key technology of robot off-line programming system, is studied. The main contents of this paper are as follows: 1. Firstly, this paper studies an algorithm of path generation for STL model based on balanced binary tree dynamic search. STL format file contains the surface information of the surface to be processed and can be used as the source file to obtain the path. The STL model containing the surface to be machined is obtained by 3D CAD modeling, then the triangulated surface of the STL model is intersected by several parallel tangent planes, and the data set of the path is obtained by the intersection of the slicing plane and the triangulated surface. The balanced binary tree dynamic search algorithm is used to optimize and sort these disordered data points to form a complete path line. Secondly, this paper uses the inverse algorithm of three NURBS curves to optimize the path. According to the slicing algorithm of STL model, the path is connected by scattered points with irregular distribution. In order to make the path more coherent, the original path is optimized by using three NURBS curves. An adaptive parameterization algorithm is proposed to determine the node vector. When the path type value points are known, the node vector and control point. 3, which can accurately describe the cubic NURBS curve of the path, are obtained. In this paper, the trajectory planning of robot based on chord-truncated iteration method is studied. Based on the known expression of the cubic NURBS curve which can accurately describe the path, the node parameters at the interpolation point are predicted according to the error of the bow height, and the real node parameters are obtained by iterating the predicted node parameters by using the chord section iteration method. The fluctuation rate between ideal velocity and actual velocity is guaranteed to be within a certain range. Finally, a trajectory generation system is developed by using MFC and Open GL techniques. According to the algorithms of path generation, path optimization and trajectory planning studied in this paper, the system architecture, system interface and module functions are proposed, and the proposed robot motion trajectory generation method is verified. The STL model of monkey carving was imported into the system to generate the robot motion trajectory and processed in practice, and compared with the motion trajectory obtained only based on the STL slicing algorithm, the validity of the proposed algorithm was verified.
【學位授予單位】：廣東工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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本文編號：1817067